Identification of the Social Duality: Street Criminality and High Vehicle Traffic in Lima City by Using Artificial Intelligence Through the Fisher-Snedecor Statistics and Shannon’s Entropy

Abstract

When Shannon’s entropy and Fisher-Snedecor statistics are working together, this can enter into a scheme of artificial intelligence to tackle social problems such as the identification of worrisome spatial points where street criminality and vehicle’s chaos is happening sharply. In this paper we construct a computational scheme to anticipate these abnormal social events. For this end we use Google-earth maps. The Fischer-Snedecor and Shannon’s entropy mathematical machinery have served to build schemes of probabilities to identify these social events. When computational simulations are done we perform matching of output ‘s simulation and official data. For the case of Lima city our modeling matches the one from real data with an accuracy of order of 85%. This result is translated as the capability of the stochastic models to analyze and measure social abnormalities such as street criminality and vehicle traffic in large cities using artificial intelligence in conjunction to stochastic formalisms.